Effects of intracolony variability in behavioral development on plasticity of division of labor in honey bee colonies

There is a genetic component to plasticity in age polyethism in honey bee colonies, such that workers of some genotypes become precocious foragers more readily than do workers of other genotypes, in colonies lacking older bees. Using colonies composed of workers from two identifiable genotype groups, we determined that intracolony differences in the likelihood of becoming a precocious forager are a consequence of differences in rates of behavioral development that are also evident under conditions leading to normal development. An alternative hypothesis, that differences in the likelihood of becoming a precocious forager are due to differences in general sensitivity to altered colony conditions, was not supported. In three out of three trials, workers from the genotype group that was more likely to exhibit precocious foraging in single cohort colonies also foraged at relatively younger ages in colonies in which workers exhibited normal behavioral development. In contrast, in three out of three trials, workers from the genotype group that was more likely to exhibit precocious foraging in single-cohort colonies did not show disproportionately more overaged nursing in colonies in which workers exhibited delayed development. These results indicate that genotypic differences in plasticity in age-related division of labor are based on genotypic differences in rates of behavioral development.     

Variability of turbulence dispersion characteristics during heavy haze process: A case study in Beijing

The turbulent standard deviations and the turbulent third-order and fourth-order moments are the key turbulence dispersion parameters in Lagrangian dispersion models. However, the characteristics of these parameters under heavy haze conditions in urban areas have not been fully investigated, and the commonly used similarity relations of these parameters in models were based on observations in highly flat and sparsely populated areas. In this paper, the vertical profiles of these parameters and their local similarity relations under heavy haze conditions in the wintertime of Beijing have been analyzed by using data collected at a 325-m meteorological tower. The heavy haze process has been divided into three stages: transport stage (TS), cumulative stage (CS), and dispersion stage (DS). Results show that the turbulent dispersion parameters behave differently during three stages. In the TS and DS, the maxima appear in the profiles of the turbulent standard deviations above the urban canopy; in the CS, the turbulent standard deviation are almost constant with height. The analysis of the third and fourth order moments shows that the wind velocities above the urban canopy in the TS deviate from the Gaussian distribution more significantly than those in the CS and DS. The local similarity relations of the turbulent dispersion parameters in the TS, especially for the longitudinal wind components, are normally different from those in the CS and DS. Thus, different from the common assumptions in Lagrangian models, the turbulence dispersion in horizontal directions is anisotropic and should be parameterized by multiple similarity relations under heavy haze conditions.     

基于改进FWA-NN的污水处理过程溶解氧浓度预测

为实现对污水处理过程溶解氧质量浓度的实时准确预测,提出了一种改进的混沌烟花混合优化算法并构建了基于改进算法的神经网络在线软测量模型.结合污水处理过程的数据特征,定义了一项新的样本相似度衡量指标用于提取更具代表性的建模数据.在改进算法中,为提高基本烟花算法初始成员的质量,定义了一种改进的两级正弦混沌映射并利用混沌运动的遍历性精选烟花算法的初始群成员;通过融合混沌算法改进了基本烟花算法的搜索机制,基于设定准则将寻优过程分为两阶段并采用两分群同时进行.测试结果表明改进算法的收敛速度和收敛精度有较大程度提高.将改进的软测量建模方法和样本数据提取方法用于污水处理过程溶解氧质量浓度软测量建模,应用结果表明该模型的均方根误差和平均泛化误差分别为0.0175和0.0118,具有较强的泛化性能.     

民航不安全事件报告危险源识别模型

为了识别民航不安全事件的发生原因,从民航不安全事件报告出发,提出了一种基于LDA主题模型和Word2Vec模型的民航不安全事件报告危险源识别模型。首先,构建危险源标签分类表,选取民航不安全事件报告与Wiki中文数据库作为数据源,然后利用LDA主题模型得出民航不安全事件报告的主题概率分布与词概率分布,最后利用Wiki中文数据库训练Word2Vec模型得到词向量,进而计算文档主题与不同危险源标签之间的相似度,得出民航不安全事件报告的危险源分类。结果表明,该模型的精准率为77.7%、召回率为86.8%、F为82.0%,能够有效识别各民航不安全事件报告的危险源。     

洪水作用下汽车的起动流速研究

针对洪水作用下汽车的起动条件开展了一系列的研究:首先分析部分淹没状态下汽车的受力情况,结合滑动平衡的临界起动条件建立相关方程,导出了洪水中汽车起动流速公式;然后在室内水槽中对三款模型车进行了一系列的起动试验。试验结果表明:对于同一款模型车,平行于水流方向放置时,起动流速与水深的相关性较好;并且水深越大,起动流速越小。接着运用试验资料率定了起动流速公式中的相关参数。最后采用模型相似率及率定后的计算公式估算了原型车辆在不同水深下的起动流速,两种方法所得的结果较为接近,故预测结果较为可靠。     

中国西南不同湿地类型水鸟多样性评价

水鸟是反映湿地生态系统健康的指标之一,对不同湿地水鸟多样性进行评价能提出有利于湿地生态系统健康良性发展的湿地管理措施,亦能更好地保护水鸟资源。为缓解近年来中国自然湿地退化和消失的问题,中国政府积极推进实施了大量修复自然湿地和新建人工湿地的工程。然而受限于人力、物力和经费,当前对自然湿地和人工湿地水鸟多样性的系统调查和评价多局限于单一地点或局部区域。因水鸟的分布具有地域性,从地域尺度进行不同湿地类型水鸟多样性评价将更为客观,公众科学数据为区域大尺度数据获取提供了可能。本研究借助中国观鸟记录中心数据,比较了2014年1月至2018年2月中国西南4省(市)自然湿地和人工湿地的水鸟物种多样性和组成相似性;结果共记录到9目19科139种水鸟,其中有94.96%的物种分布于自然湿地,67.63%的物种分布于人工湿地;各类群水鸟在自然湿地中的物种数均高于人工湿地。结果说明自然湿地在水鸟保护中具有重要栖息地功能,人工湿地能为大部分水鸟提供栖息地,但不能完全代替自然湿地。自然湿地中的湖泊湿地、河流湿地和沼泽化草甸以及人工湿地中的水库、城市人工景观水面和娱乐水面是水鸟,特别是受威胁水鸟分布的重要湿地类型;建议政府部门重点对上述湿地亚类进行合理的规划和管理。     

长沙市两种空气质量预报方法检验对比

为探索新的空气质量预报方法，提高预报准确率，采用统计和对比方法，分析了长沙市空气质量现状，介绍了天气形势相似及动态逐步回归两种空气质量统计预报方法，并对其一年多的运行结果进行了检验和对比。结果表明，长沙市空气污染主要由PM\-\{10\}和SO\-2浓度超标引起, 且具有明显的空间分布特征;5年来长沙城市空气质量明显好转;两种预报方法对各污染物都有一定的预报能力，预报的误差绝对值多集中在30以内，而级别误差基本上在1级以内。两种方法对NO\-2的预报准确率均在98%左右,预报效果优良。绝对误差对比发现，两种预报方法对SO\-2的预报明显优于PM\-\{10\}预报；级别准确率对比时，两种预报方法对3种污染物的预报准确率相近。两种预报方法对3个污染因子的预报准确率呈现出NO\-2优于SO\-2优于PM\-\{10\}的趋势。     

粉煤灰中氨氮的测定方法研究

从浸提、干扰去除和显色3个方面对纳氏试剂分光光度法进行优化改进,建立了一种用于粉煤灰中氨氮测定的适宜方法,并利用浸提完全度和精密度实验对该方法了进行了评价。优化后的方法为:按固液比1∶10加入0.05 mol/L H_2SO_4振荡浸提30 min,再加入1.5 mL酒石酸钾钠溶液(500 g/L)和1.5 mL NaOH溶液(5 mol/L)去除金属离子干扰,最后加入1.5 mL纳氏试剂进行显色。粉煤灰浸提后残渣的蒸馏液中未检测出氨氮,说明浸提效果较为完全。同一样品的8次平行测定结果的相对标准偏差为6.10%,说明该方法稳定可靠。     

Optimization of thermal performance of the parabolic trough solar collector systems based on GA-BP neural network model

The aim of this paper is to optimize the thermal performance (system output energy, thermal efficiency, and heat loss of cavity absorber) of parabolic trough solar collector (PTC) systems in order to improve its thermal performance, based on the genetic algorithm-back propagation (GA-BP) neural network model. There are a number of undefined problems, fuzzy or incomplete information and a complex thermal performance of the PTC systems. Therefore, the thermal performance prediction of the PTC systems based on GA-BP neural network model was developed. Subsequently, the metrics performances have been adopted to comprehensively understand the algorithm and evaluate the prediction accuracy. Results revealed that the GA-BP neural network model can be successfully used to predict the complex nonlinear relationship between the input variables and thermal performance of the PTC systems. The cosine effect has a great influence on the thermal performance; thereby the geometrical structure of the PTC systems was optimized. It was found that the optimized geometrical structure was beneficial to improve the thermal performance of the PTC system. In conclusion, the GA-BP neural network model has higher prediction accuracy than the other algorithm and it can be feasible and reliable.     

A generalized analytical solution for turbulent dispersion with inhomogeneous wind and diffusion coefficient

A technique is presented to solve analytically the turbulent diffusion equation for the concentration of a passive contaminant emitted from an elevated continuous source into the atmosphere. A generalized method of solution using Sturm–Liouville and WKB theories is developed to overcome difficulties due to the height‐dependent wind velocity and diffusion coefficient appearing in the diffusion equation. The method presented in this paper is able to derive an asymptotic expression for the concentration obtained from the solution of the atmospheric diffusion equation which involves explicitly inhomogeneous wind velocity and diffusion coefficient. The diffusion equation model derived from this method can be applied in a practical prediction of contaminant concentration in a turbulent atmosphere. This revised version was published online in August 2006 with corrections to the Cover Date.